Using the AWS Graph Explorer with Fuseki and local datasets

An open source visual graph navigator.

When I first heard about the AWS Graph Explorer I assumed that it was a cloud-based tool for use with Neptune, the AWS cloud-based triplestore. After I read Fan Li’s First Impressions of the AWS Graph Explorer I realized that you can install this open source tool locally and point it at any SPARQL endpoint you want, so I cranked up Jena Fuseki on my laptop, loaded some data into it, and installed the Graph Explorer.

There are a few tutorials out there about how to start up your own free-tier Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instance and then run your own publicly available web server. I’ve planned for a while to try this with a Jena Fuseki triplestore and SPARQL endpoint, but I postponed it because I thought it might be complicated. It turned out to be pretty easy.

More Picasso paintings in one year than all the Vermeer paintings?

Answering an art history question with SPARQL.

Sometimes a question pops into my head that, although unrelated to computers, could likely be answered with a SPARQL query. I don’t necessarily know the query off the top of my head and have to work it out. I’m going to discuss an example of one that I worked out and the steps that I took, because I wanted to show how I navigated the Wikidata data model to get what I wanted.

Two recent articles describe a fascinating use of SPARQL to improve data quality in a knowledge graph at the successful grocery delivery service Instacart. On Reliability Scores for Knowledge Graphs (pdf) is a short paper submitted to the 2022 ACM Web Conference in Lyon and a longer piece on Instacart’s tech blog is titled Red Means Stop. Green Means Go: A Look into Quality Assessment in Instacart’s Knowledge Graph.